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Update parquet files
Browse files- README.md +0 -213
- dataset_infos.json +0 -1
- default/qa_zre-test.parquet +3 -0
- default/qa_zre-train-00000-of-00005.parquet +3 -0
- default/qa_zre-train-00001-of-00005.parquet +3 -0
- default/qa_zre-train-00002-of-00005.parquet +3 -0
- default/qa_zre-train-00003-of-00005.parquet +3 -0
- default/qa_zre-train-00004-of-00005.parquet +3 -0
- default/qa_zre-validation.parquet +3 -0
- qa_zre.py +0 -99
README.md
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---
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annotations_creators:
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- no-annotation
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language_creators:
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- expert-generated
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language:
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- en
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license:
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- unknown
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multilinguality:
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- monolingual
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pretty_name: QaZre
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size_categories:
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- 1M<n<10M
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source_datasets:
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- original
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task_categories:
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- question-answering
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task_ids: []
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paperswithcode_id: null
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tags:
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- zero-shot-relation-extraction
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dataset_info:
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features:
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- name: relation
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dtype: string
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- name: question
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dtype: string
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- name: subject
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dtype: string
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- name: context
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dtype: string
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- name: answers
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sequence: string
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splits:
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- name: test
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num_bytes: 29410194
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num_examples: 120000
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- name: validation
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num_bytes: 1481430
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num_examples: 6000
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- name: train
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num_bytes: 2054954011
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num_examples: 8400000
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download_size: 516061636
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dataset_size: 2085845635
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---
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# Dataset Card for QaZre
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## Table of Contents
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Annotations](#annotations)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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- **Homepage:** [http://nlp.cs.washington.edu/zeroshot](http://nlp.cs.washington.edu/zeroshot)
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- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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- **Size of downloaded dataset files:** 492.15 MB
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- **Size of the generated dataset:** 1989.22 MB
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- **Total amount of disk used:** 2481.37 MB
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### Dataset Summary
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A dataset reducing relation extraction to simple reading comprehension questions
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### Supported Tasks and Leaderboards
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Languages
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## Dataset Structure
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### Data Instances
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#### default
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- **Size of downloaded dataset files:** 492.15 MB
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- **Size of the generated dataset:** 1989.22 MB
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- **Total amount of disk used:** 2481.37 MB
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An example of 'validation' looks as follows.
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```
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{
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"answers": [],
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"context": "answer",
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"question": "What is XXX in this question?",
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"relation": "relation_name",
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"subject": "Some entity Here is a bit of context which will explain the question in some way"
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}
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```
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### Data Fields
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The data fields are the same among all splits.
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#### default
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- `relation`: a `string` feature.
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- `question`: a `string` feature.
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- `subject`: a `string` feature.
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- `context`: a `string` feature.
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- `answers`: a `list` of `string` features.
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### Data Splits
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| name | train | validation | test |
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|---------|--------:|-----------:|-------:|
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| default | 8400000 | 6000 | 120000 |
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## Dataset Creation
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### Curation Rationale
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Source Data
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#### Initial Data Collection and Normalization
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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#### Who are the source language producers?
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Annotations
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#### Annotation process
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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#### Who are the annotators?
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Personal and Sensitive Information
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Discussion of Biases
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Other Known Limitations
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## Additional Information
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### Dataset Curators
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Licensing Information
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Unknown.
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### Citation Information
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```
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@inproceedings{levy-etal-2017-zero,
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title = "Zero-Shot Relation Extraction via Reading Comprehension",
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author = "Levy, Omer and
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Seo, Minjoon and
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Choi, Eunsol and
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Zettlemoyer, Luke",
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booktitle = "Proceedings of the 21st Conference on Computational Natural Language Learning ({C}o{NLL} 2017)",
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month = aug,
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year = "2017",
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address = "Vancouver, Canada",
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publisher = "Association for Computational Linguistics",
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url = "https://www.aclweb.org/anthology/K17-1034",
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doi = "10.18653/v1/K17-1034",
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pages = "333--342",
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}
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```
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### Contributions
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Thanks to [@thomwolf](https://github.com/thomwolf), [@lhoestq](https://github.com/lhoestq), [@ghomasHudson](https://github.com/ghomasHudson), [@lewtun](https://github.com/lewtun) for adding this dataset.
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dataset_infos.json
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{"default": {"description": "A dataset reducing relation extraction to simple reading comprehension questions\n", "citation": "@inproceedings{levy-etal-2017-zero,\n title = \"Zero-Shot Relation Extraction via Reading Comprehension\",\n author = \"Levy, Omer and\n Seo, Minjoon and\n Choi, Eunsol and\n Zettlemoyer, Luke\",\n booktitle = \"Proceedings of the 21st Conference on Computational Natural Language Learning ({C}o{NLL} 2017)\",\n month = aug,\n year = \"2017\",\n address = \"Vancouver, Canada\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://www.aclweb.org/anthology/K17-1034\",\n doi = \"10.18653/v1/K17-1034\",\n pages = \"333--342\",\n}\n", "homepage": "http://nlp.cs.washington.edu/zeroshot", "license": "", "features": {"relation": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "subject": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "supervised_keys": null, "builder_name": "qa_zre", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "datasets_version_to_prepare": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 29410194, "num_examples": 120000, "dataset_name": "qa_zre"}, "validation": {"name": "validation", "num_bytes": 1481430, "num_examples": 6000, "dataset_name": "qa_zre"}, "train": {"name": "train", "num_bytes": 2054954011, "num_examples": 8400000, "dataset_name": "qa_zre"}}, "download_checksums": {"http://nlp.cs.washington.edu/zeroshot/relation_splits.tar.bz2": {"num_bytes": 516061636, "checksum": "e33d0e367b6e837370da17a2d09d217e0a92f8d180f7abb3fd543a2d1726b2b4"}}, "download_size": 516061636, "dataset_size": 2085845635, "size_in_bytes": 2601907271}}
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default/qa_zre-test.parquet
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qa_zre.py
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"""A dataset reducing relation extraction to simple reading comprehension questions"""
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import csv
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import os
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import datasets
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_CITATION = """\
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@inproceedings{levy-etal-2017-zero,
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title = "Zero-Shot Relation Extraction via Reading Comprehension",
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author = "Levy, Omer and
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Seo, Minjoon and
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Choi, Eunsol and
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Zettlemoyer, Luke",
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booktitle = "Proceedings of the 21st Conference on Computational Natural Language Learning ({C}o{NLL} 2017)",
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month = aug,
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year = "2017",
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address = "Vancouver, Canada",
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publisher = "Association for Computational Linguistics",
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url = "https://www.aclweb.org/anthology/K17-1034",
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doi = "10.18653/v1/K17-1034",
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pages = "333--342",
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}
|
25 |
-
"""
|
26 |
-
|
27 |
-
_DESCRIPTION = """\
|
28 |
-
A dataset reducing relation extraction to simple reading comprehension questions
|
29 |
-
"""
|
30 |
-
|
31 |
-
_DATA_URL = "http://nlp.cs.washington.edu/zeroshot/relation_splits.tar.bz2"
|
32 |
-
|
33 |
-
|
34 |
-
class QaZre(datasets.GeneratorBasedBuilder):
|
35 |
-
"""QA-ZRE: Reducing relation extraction to simple reading comprehension questions"""
|
36 |
-
|
37 |
-
VERSION = datasets.Version("0.1.0")
|
38 |
-
|
39 |
-
def _info(self):
|
40 |
-
return datasets.DatasetInfo(
|
41 |
-
description=_DESCRIPTION,
|
42 |
-
features=datasets.Features(
|
43 |
-
{
|
44 |
-
"relation": datasets.Value("string"),
|
45 |
-
"question": datasets.Value("string"),
|
46 |
-
"subject": datasets.Value("string"),
|
47 |
-
"context": datasets.Value("string"),
|
48 |
-
"answers": datasets.features.Sequence(datasets.Value("string")),
|
49 |
-
}
|
50 |
-
),
|
51 |
-
# If there's a common (input, target) tuple from the features,
|
52 |
-
# specify them here. They'll be used if as_supervised=True in
|
53 |
-
# builder.as_dataset.
|
54 |
-
supervised_keys=None,
|
55 |
-
# Homepage of the dataset for documentation
|
56 |
-
homepage="http://nlp.cs.washington.edu/zeroshot",
|
57 |
-
citation=_CITATION,
|
58 |
-
)
|
59 |
-
|
60 |
-
def _split_generators(self, dl_manager):
|
61 |
-
"""Returns SplitGenerators."""
|
62 |
-
dl_dir = dl_manager.download_and_extract(_DATA_URL)
|
63 |
-
dl_dir = os.path.join(dl_dir, "relation_splits")
|
64 |
-
|
65 |
-
return [
|
66 |
-
datasets.SplitGenerator(
|
67 |
-
name=datasets.Split.TEST,
|
68 |
-
gen_kwargs={
|
69 |
-
"filepaths": [os.path.join(dl_dir, "test." + str(i)) for i in range(10)],
|
70 |
-
},
|
71 |
-
),
|
72 |
-
datasets.SplitGenerator(
|
73 |
-
name=datasets.Split.VALIDATION,
|
74 |
-
gen_kwargs={
|
75 |
-
"filepaths": [os.path.join(dl_dir, "dev." + str(i)) for i in range(10)],
|
76 |
-
},
|
77 |
-
),
|
78 |
-
datasets.SplitGenerator(
|
79 |
-
name=datasets.Split.TRAIN,
|
80 |
-
gen_kwargs={
|
81 |
-
"filepaths": [os.path.join(dl_dir, "train." + str(i)) for i in range(10)],
|
82 |
-
},
|
83 |
-
),
|
84 |
-
]
|
85 |
-
|
86 |
-
def _generate_examples(self, filepaths):
|
87 |
-
"""Yields examples."""
|
88 |
-
|
89 |
-
for file_idx, filepath in enumerate(filepaths):
|
90 |
-
with open(filepath, encoding="utf-8") as f:
|
91 |
-
data = csv.reader(f, delimiter="\t")
|
92 |
-
for idx, row in enumerate(data):
|
93 |
-
yield f"{file_idx}_{idx}", {
|
94 |
-
"relation": row[0],
|
95 |
-
"question": row[1],
|
96 |
-
"subject": row[2],
|
97 |
-
"context": row[3],
|
98 |
-
"answers": row[4:],
|
99 |
-
}
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